Voice AI Engineer (Real-Time Speech) (#5861)

Technical Level: Senior

Job Category: Software Development

Project: Leading regional mobile network operator We are looking for a Voice AI Engineer (Real-time speech)to join our team! Our clientis an Azerbaijani telecommunications company and Azerbaijan's largest mobile network operator. The main products are: Fixed telephony, Mobile telephony, Internet services, Wireless broadband, and Value-added services. The primary goal is to accelerate the client’s Data & AI initiatives via a secure, hybrid cloud foundation on AWS while systematically modernizing the IT estate as part of the AWS MAP 2.0 program. Key Project Objectives include: Cloud Foundation & Landing Zone: Deploy target hybrid network architectures, establishing a secure AWS Landing Zone Accelerator (LZA) and hybrid Data/AI platforms on AWS. Security, Compliance & Sovereignty: Operationalize on-premises data de-identification and Format Preserving Encryption (FPE) tokenization (achieving zero raw PII in the cloud), fully adhering to Azerbaijani Personal Data Law No. 998-IIIQ and Critical Information Infrastructure Rules (Resolution No. 229). AI Chatbot & Real-Time Voicebot Implementation: Develop and operationalize a flagship Customer Care Voicebot (STT → LLM → TTS pipeline) and Agentic Chatbot targetingResponsibilities: Design, build, and operationalize end-to-end real-timeSTT → LLM → TTS (Speech-to-Text / LLM / Text-to-Speech)voicebot pipelines on AWS, optimizing for streaming speech-to-text, first-token LLM generation, and first-audio TTS synthesis. Deploy and maintain production customer-trainedWhisper (Azerbaijani ASR)andAzerbaijani TTSmodels as low-latency real-time endpoints onAmazon SageMakerand specialized GPU node pools (NVIDIA A100/L40S). Implement and manage the Bedrock Proxy Gatewayon EKS for multi-model routing, priority queuing via Redis Sorted Sets, cost caps, and high-availability serving targeting ~200 rps without API throttling. Integrate voicebot and chatbot decision engines with core enterprise telephony and CVM platforms, including Avaya(voice telephony), Genesys(digital chat/omnichannel), andPelatro(CVM offer decisioning and uplift models). Establish LLMOps & MLOpspipelines usingAmazon SageMaker PipelinesandMLflowfor experiment tracking, model versioning, prompt/agent registries, automated evaluation harnesses, and RAG knowledge base retrieval. Build call and chat transcription pipelines to ingest, transcribe, and extract real-time insights (churn risk, dissatisfaction, intent, lead signals) into downstream decision layers. Enforce data sovereignty and privacy controls by integrating on-premises Format Preserving Encryption (FPE)and tokenization wrappers into ML pipelines so zero raw PII enters AWS cloud environments. Define NFR baselines, dialogue flows, voicebot persona, turn-taking, and fallback/escalation logic to guarantee conversational round-trip latencyAutomate ML deployment workflows using GitLab CI/CDand Infrastructure-as-Code ( TerraformorAWS CDK ), establishing observability and FinOps spend/anomaly monitoring viaAmazon CloudWatchandSplunk.

Requirements: 4+ years of hands-on experience with machine learning and Speech Processing with a primary focus on real-time conversational AI, ASR (STT), andTTSvoice pipelines. Deep expertise withAmazon SageMaker(real-time GPU inference endpoints, Pipelines, Feature Store, Model Registry) andAmazon Bedrock(AgentCore, Bedrock Guardrails, Knowledge Bases). Proven track record in streaming speech inference, speech synthesis, and low-latency audio processing. Strong experience inGPU optimizationand containerized orchestration (NVIDIA A100/L40S, AWS EC2 GPU instances, Docker, Kubernetes/EKS). Solid understanding of contact center and telephony platform integrations ( Avaya , Genesys ) and real-time decisioning interfaces. Proficient in Python, Redis (priority queuing & caching), and data security/privacy (FPE tokenization, handling sensitive/PII data). Nice-to-have skills: AWS Certified Machine Learning – SpecialtyorAWS Certified Solutions Architect. Hands-on experience with EMR-on-EKS, Apache Iceberg, or MSK (Kafka) streaming pipelines. Soft Skills & Team Fit: Strong critical thinking, problem-solving, and analytical skills with ownership of mission-critical, low-latency deliverables. Excellent communication and collaboration skills to work closely with cross-functional teams (AI Architects, Data Engineers, CC SMEs, and Security/Compliance). Results-oriented, proactive mindset with strong ownership within an Agile / Scrum framework. Upper-Intermediate+ English level (written and spoken). We offer*: Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing

Project: Leading regional mobile network operator

Project: Global biopharmaceutical company